Cognitive Bias in User Research
A cognitive bias is a type of inaccuracy in thinking that occurs as people process and interpret information from the world around them, influencing their actions and judgments. Cognitive biases can have a impact on product design. Cognitive biases can affect team members’ judgements and product design decisions by leading them to make a systematic error in thinking. When designers create a theory about how something should operate for their audience and want to validate that hypothesis through user research, cognitive bias can occur. Overcoming cognitive biases during user research will help you to improve the efficiency of your product design.
Below are some common cognitive biases in User Research:
- Framing Effect
People will react differently to the same information depending on how it’s worded, so people not only focus on their genuine opinion of the product instead.
Example: Replace question “Do you enjoy this feature?” with “What do you think about this feature?”
- Confirmation Bias
Confirmation bias occurs “when you have an interpretation, accept it, and then, top-down, you push everything to suit that explanation,” according to psychologist Daniel Kahneman, who coined the term. Some UX researcher ignore pain points that people are experiencing during user research since they don’t fit with your existing assumptions.
Example: Users may complain to a UX researcher about a product’s poorly designed navigation system. Because the design appears rational to them, a UX researcher may ignore such input.
- Social Desirability Bias
When people are around other people, they tend to make more “socially acceptable” decisions. When left alone and functioning independently, a person’s behavior may be radically different.
Example: During interviews might not be valid because test participants want to give desirable answers. As much as possible try to observe users in their real environments with the same conditions in which they would be using the product.
- The Recency Effect
People tend to give their most recent experiences significantly. The recency effect causes UX practitioners to create fresh perspectives that are biased toward the most recent news.
Example: When a UX researcher conducts a series of usability testing, they might focus more on the problems found in the latest session.
- Clustering Illusion
Data clustering is the process of grouping or thematically organizing huge amounts of data based on their links.
Example: A drawback of qualitative analysis is that with such a short sample size, it is often impossible to avoid seeing patterns that might be just smaller sets of randomness that appear to have a commonality.